

'''simple docstring'''
import argparse
from pathlib import Path

from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration


def  a__       (    _SCREAMING_SNAKE_CASE   :       List[Any]	,				_SCREAMING_SNAKE_CASE   :       str	,				_SCREAMING_SNAKE_CASE   :       str	,				_SCREAMING_SNAKE_CASE   :       Path	,				_SCREAMING_SNAKE_CASE   :       str = None	,				_SCREAMING_SNAKE_CASE   :       str = None	,				_SCREAMING_SNAKE_CASE   :       str = None	,				)     ->					Optional[int]:


	"""simple docstring"""





	if config_name_or_path is None:
		UpperCAmelCase_     :      List[str]						=  "facebook/rag-token-base" if model_type == "rag_token" else "facebook/rag-sequence-base"

	if generator_tokenizer_name_or_path is None:
		UpperCAmelCase_     :      Any						=  generator_name_or_path

	if question_encoder_tokenizer_name_or_path is None:
		UpperCAmelCase_     :      int						=  question_encoder_name_or_path

	UpperCAmelCase_     :      Optional[Any]						=  RagTokenForGeneration if model_type == "rag_token" else RagSequenceForGeneration

	# Save model.
	UpperCAmelCase_     :      List[str]						=  RagConfig.from_pretrained(_SCREAMING_SNAKE_CASE				)
	UpperCAmelCase_     :      Optional[int]						=  AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE				)
	UpperCAmelCase_     :      Dict						=  AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE				)

	UpperCAmelCase_     :      Optional[Any]						=  gen_config
	UpperCAmelCase_     :      str						=  question_encoder_config

	UpperCAmelCase_     :      Tuple						=  model_class.from_pretrained_question_encoder_generator(
	    _SCREAMING_SNAKE_CASE	,				_SCREAMING_SNAKE_CASE	,				config=_SCREAMING_SNAKE_CASE				)
	rag_model.save_pretrained(_SCREAMING_SNAKE_CASE				)

	# Sanity check.
	model_class.from_pretrained(_SCREAMING_SNAKE_CASE				)

	# Save tokenizers.
	UpperCAmelCase_     :      str						=  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE				)
	gen_tokenizer.save_pretrained(dest_dir / "generator_tokenizer/"				)
	UpperCAmelCase_     :      List[str]						=  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE				)
	question_encoder_tokenizer.save_pretrained(dest_dir / "question_encoder_tokenizer/"				)


if __name__ == "__main__":
					_lowerCamelCase      					=     argparse.ArgumentParser()
					parser.add_argument(
					    """--model_type""",
					    choices=["""rag_sequence""", """rag_token"""],
					    required=True,
					    type=str,
					    help="""RAG model type: rag_sequence, rag_token""",
					)
					parser.add_argument("""--dest""", type=str, required=True, help="""Path to the output checkpoint directory.""")
					parser.add_argument("""--generator_name_or_path""", type=str, required=True, help="""Generator model identifier""")
					parser.add_argument(
					    """--question_encoder_name_or_path""", type=str, required=True, help="""Question encoder model identifier"""
					)

					parser.add_argument(
					    """--generator_tokenizer_name_or_path""",
					    type=str,
					    help="""Generator tokenizer identifier, if not specified, resolves to ``generator_name_or_path``""",
					)
					parser.add_argument(
					    """--question_encoder_tokenizer_name_or_path""",
					    type=str,
					    help="""Question encoder tokenizer identifier, if not specified, resolves to ``question_encoder_name_or_path``""",
					)
					parser.add_argument(
					    """--config_name_or_path""",
					    type=str,
					    help=(
					        """Identifier of the model config to use, if not provided, resolves to a base config for a given"""
					        """ ``model_type``"""
					    ),
					)

					_lowerCamelCase      					=     parser.parse_args()

					_lowerCamelCase      					=     Path(args.dest)
					dest_dir.mkdir(exist_ok=True)

					consolidate(
					    args.model_type,
					    args.generator_name_or_path,
					    args.question_encoder_name_or_path,
					    dest_dir,
					    args.config_name_or_path,
					    args.generator_tokenizer_name_or_path,
					    args.question_encoder_tokenizer_name_or_path,
					)








import requests

_SCREAMING_SNAKE_CASE     :					Optional[int]      =       ""  # <-- Put your OpenWeatherMap appid here!
_SCREAMING_SNAKE_CASE     :					Optional[Any]      =       "https://api.openweathermap.org/data/2.5/"
def      UpperCAmelCase__		(UpperCamelCase_ = "Chicago"				,UpperCamelCase_ = APPID							):



     """simple docstring"""






     return requests.get(URL_BASE + '''weather'''				,params=locals()							).json()
def      UpperCAmelCase__		(UpperCamelCase_ = "Kolkata, India"				,UpperCamelCase_ = APPID							):



     """simple docstring"""






     return requests.get(URL_BASE + '''forecast'''				,params=locals()							).json()
def      UpperCAmelCase__		(UpperCamelCase_ = 55.68				,UpperCamelCase_ = 12.57				,UpperCamelCase_ = APPID							):



     """simple docstring"""






     return requests.get(URL_BASE + '''onecall'''				,params=locals()							).json()


if __name__ == "__main__":
 from pprint import pprint

 while True:
  _SCREAMING_SNAKE_CASE     :					Any      =       input("Enter a location:").strip()
  if location:
   pprint(current_weather(location))
  else:
   break




